Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms and applications of cognition, management, and control for complex systems
Fei-Yue WANG1, Jianbo GUO2, Guangquan BU3, Jun Jason ZHANG4()
1. The State Key Laboratory for Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China 2. State Grid Cooperation of China, Beijing 100031, China 3. China Electric Power Research Institute, Beijing 100192, China 4. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
In this paper, we aim to illustrate the concept of mutually trustworthy human-machine knowledge automation (HM-KA) as the technical mechanism of hybrid augmented intelligence (HAI) based complex system cognition, management, and control (CMC). We describe the historical development of complex system science and analyze the limitations of human intelligence and machine intelligence. The need for using human-machine HAI in complex systems is then explained in detail. The concept of “mutually trustworthy HM-KA” mechanism is proposed to tackle the CMC challenge, and its technical procedure and pathway are demonstrated using an example of corrective control in bulk power grid dispatch. It is expected that the proposed mutually trustworthy HM-KA concept can provide a novel and canonical mechanism and benefit real-world practices of complex system CMC.
王飞跃, 郭剑波, 卜广全, 张俊. 人机互信的知识自动化与混合增强智能：复杂系统认知管控机制及其应用[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(8): 1142-1157.
Fei-Yue WANG, Jianbo GUO, Guangquan BU, Jun Jason ZHANG. Mutually trustworthy human-machine knowledge automation and hybrid augmented intelligence: mechanisms and applications of cognition, management, and control for complex systems. Front. Inform. Technol. Electron. Eng, 2022, 23(8): 1142-1157.
